Resume Screener 📄🔍

Welcome to the Resume Screener project! This project aims to predict the role of a candidate based on their uploaded resume. It's built using Natural Language Processing (NLP) techniques and deployed as a web application using Streamlit.

How it Works

Upload Resume: Users can upload their resume in either .txt or .pdf format using the file uploader provided in the web application.

Prediction: The uploaded resume is then processed using NLP techniques to extract relevant features. These features are used to make predictions about the role of the candidate.

Display Prediction: The predicted role of the candidate is displayed to the user along with a confidence score. Additionally, the application provides a brief explanation of how the prediction was made.

Technologies Used

Streamlit: Used to build the web application interface.

Scikit-learn: Utilized for training and deploying the machine learning model.

NLTK: Used for text preprocessing tasks such as tokenization and stopword removal.

Joblib and Pickle: Used for serializing and deserializing the trained model and vectorizer.

Git: Version control system used for managing project files.

App : https://resumescreneer-by-bheesettianand.streamlit.app/